As a main branch of weakly supervised learning paradigm, partial label learning (PLL)
copes with the situation where each sample corresponds to ambiguous candidate labels …

In recent years, Aspect-based Sentiment Analysis (ABSA) has been a crucial yet challenging
task in recognizing textual emotions from text. ABSA has numerous application across …

Cohesion is one of the main defining characteristics of textuality. There is a lack of
approaches to textual cohesion benefiting from both high computational implementability …

Abstract Multi-Label Text Classification (MLTC) is one of the most import research of natural
language processing. Although Deep Learning (DL) models have been widely applied to …

Short texts on social platforms often have the problems of diverse categories and semantic
sparsity, making it challenging to identify the diverse intentions of users. To address this …

Given the complicated label hierarchy, hierarchical text classification (HTC) has emerged as
a challenging subtask in the realm of multi-label text classification. Existing methods …

Modern buildings are large and complex, and as more time is spent inside them, the risk of
indoor disasters such as fires and gas leaks increases. In the event of such a disaster, the …

In crisis situations, emergency response organizations can derive significant benefits from
actionable information available on social media. Such information provides effective …

Feature extraction can effectively alleviate the curse of dimensionality on high-dimensional
data. Contrastive learning, as a self-supervised learning method, has garnered widespread …

Many sentiment analysis methods have been proposed recently to evaluate, through the
Web, the perceptions of users and their satisfaction with the use of products and services; …